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Robots have multiple possibilities to help people with limited mobility, including colors that can help patients wear clothing. This is a very difficult task, however, requiring skill, safety and speed. Now, scientists at MIT CSAIL have developed a coherent approach to allowing non-destructive problems rather than allowing any problems as in the past.
Humans are hard-pressed to get along with humans, but robots have to learn all of this. For example, it is easy for someone to help someone to get dressed, since we know where to hold the garment, how to hold the hands, how the cloth is made, and so on. However, robots have to be equipped with all that knowledge.
In the past, algorithms forbade robots from affecting humans for security purposes. However, this could lead to something called a “cold robot”, in which the robot stops moving and cannot perform the function it was required to do.
To address this problem, the MIT CSAIL team led by PhD student Shen Li developed a method that also enhances robotic safety by allowing “complexity” at the top to avoid collisions. This allows the robot to be able to communicate with humans harmlessly in order to accomplish its mission, as long as it affects humans.
“Creating algorithms to prevent physical harm from unnecessarily affecting performance is extremely difficult,” Li said. “By allowing the robots not to be damaged by humans, our approach would be able to find the best robots to keep the person safe and secure.”
In simple terms, the system worked even though the person was doing other things such as looking at the phone, as shown in the video above. It does this by combining several different colors, instead of relying on the same color as before. “The intervention method incorporates theories, barriers to the protection of human cognition, predicting human behavior and directing feedback on robotic operations,” says Zackory Erickson University of Carnegie Mellon.
This research is still in its infancy, but the concept can be applied to other areas than just clothing. “This research can be applied to a wide range of robotic applications, with the ultimate goal of making robots more accessible to people with disabilities,” Erickson said.
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